1. Field of the Invention
The present invention relates to a geolocation technique. In particular, the present invention relates to a geolocation technique that can estimate both time-of-arrival and amplitude of the received signal using a super-resolution technique.
2. Discussion of the Related Art
The need for accurate geolocation has intensified in recent years, especially in cluttered environments (e.g., inside buildings, in urban locales, and foliage), where the Global Positioning System (GPS) is often inaccessible. Unreliable geolocation hinders various applications, for example the tracking of inventory in warehouses or cargo ships in commercial settings, and blue force tracking for locating friendly forces in military scenarios. Ultra-wideband (UWB) technology offers great potential for achieving high positioning accuracy in such cluttered environments due to its ability to resolve multipath and penetrate obstacles. Discussions of positioning using UWB technology may be found, for example, in (a) R. J. Fontana and S. J. Gunderson, “Ultra-wideband precision asset location system,” in Proc. of IEEE Conf on Ultra Wideband Systems and Technologies (UWBST), Baltimore, Md., May 2002, pp. 147-150; (b) L. Stoica, S. Tiuraniemi, A. Rabbachin, I Oppermann, “An ultra wideband TAG circuit transceiver architecture,” in International Workshop on Ultra Wideband Systems. Joint UWBST and IWUWBS 2004, Kyoto, Japan, May 2004, pp. 258-262; (c) D. Dardari, “Pseudo-random active UWB reflectors for accurate ranging,” IEEE Commun. Lett., vol. 8, no. 10, pp. 608-610, October 2004; (d) S. Gezici, Z. Tian, G. B. Giannakis, H. Kobayashi, A. F. Molisch, H. V. Poor, and Z. Sahinoglu, “Localization via ultrawideband radios: a look at positioning aspects for future sensor networks,” IEEE Signal Processing Mag., vol. 22, pp. 70-84, July 2005; and (e) Y. Qi, H. Kobayashi, and H. Suda, “Analysis of wireless geolocation in a non-line-of-sight environment,” IEEE Trans. Wireless Commun., vol. 5, no. 3, pp. 672-681, March 2006.
For localization systems based on the UWB technology, it is natural to deploy the time-of-arrival (TOA) technique in order to exploit the fine time resolution of a UWB signal. However, ranging accuracy may be limited by noise, multipath components (MPCs), the effects of system bandwidth, and non-line-of-sight (NLOS) conditions. Most ranging techniques are based on the TOA estimation of the first path. Examples of localization systems using TOA techniques include (a) K. Yu and I. Oppermann, “Performance of UWB position estimation based on time-of-arrival measurements,” in International Workshop on Ultra Wideband Systems. Joint UWBST and IWUWBS 2004, Kyoto, Japan, May 2004, pp. 400-404; (b) I. Guvenc, Z. Sahinoglu, A. F. Molisch, and P. Orlik, “Non-coherent TOA estimation in IR-UWB systems with different signal waveforms,” in Proc. IEEE Int. Workshop on Ultrawideband Networks (UWBNETS), Boston, Mass., October 2005, pp. 245-251; and (c) D. Dardari, C.-C. Chong, and M. Z. Win, “Threshold-based time-of-arrival estimators in UWB dense multipath channels,” IEEE Trans. Commun., in press (“Dardari”).
Generally, however, the first path is not necessarily the strongest path, so that an estimation of the TOA is challenging in dense multipath channels. The problem of an accurate TOA estimation in a multipath environment is closely related to the problem of channel estimation, in which channel amplitudes and TOAs can be jointly estimated using, for example, a maximum likelihood (ML) approach. ML approaches are discussed, for example, in (a) V. Lottici, A. D'Andrea, and U. Mengali, “Channel estimation for ultra-wideband communications,” IEEE J. Select. Areas Commun., vol. 20, no. 9, pp. 1638-1645, December 2002; (b) A. Rabbachin, I. Oppermann, and B. Denis, “ML time-of-arrival estimation based on low complexity UWB energy detection,” in Proc. IEEE Int. Conf. on Ultra-Wideband (ICUWB), Waltham, Mass., September 2006, pp. 599-604; (c) H. Saamisaari, “ML time delay estimation in a multipath channel,” in International Symposium on Spread Spectrum Techniques and Applications, Mainz, GERMANY, September 1996, pp. 1007-1011 (“Saarnisaari”); and (d) J.-Y. Lee and R. A. Scholtz, “Ranging in a dense multipath environment using an UWB radio link,” IEEE J. Select. Areas Commun., vol. 20, no. 9, pp. 1677-1683, December 2002 (“Lee”). Most ML estimators are complex, so as to incur high implementation costs and high power consumption.
In addition, complex channel estimators are not always good TOA estimators. In fact, for certain signal-to-noise-ratio (SNR) ranges, Saarnisaari shows that the ML channel estimator performs poorly in estimating the TOA of the first path, when compared to a simple threshold-based TOA estimator. Lee discloses a generalized ML-based TOA estimation technique that is applied to UWB, assuming that the strongest path is perfectly locked and the relative delay of the first path is estimated. Lee's UWB ranging system uses a correlator and a parallel sampler with a high-speed measurement capability in each transceiver, thereby accomplishing two-way ranging between the transceivers without a common clock. Lee's system suffers from a high implementation complexity which makes it impractical for low-cost sensor applications.
Some TOA estimation techniques estimate the strongest path and adopts the TOA of this strongest path as the estimated TOA for the received signal. As the first arriving path is not always the strongest path, especially under the NLOS condition in dense multipath channels, the resulting TOA estimates are therefore inaccurate.
Alternatively, TOA estimation can be accomplished using a peak-detection (i.e., classical correlation) estimator, where the received signal is correlated with the transmitted signal template and the position of the first detected maximum/local peak at the correlator output is regarded as the TOA. One example of this peak-detection technique is discussed in X. Chen, S. Zhang and S. Wu, “Signal time of arrival estimation method and system,” U.S. Pat. No. 6,510,186, Jan. 21, 2003 (“Chen”). Chen discloses a system including a channel estimator and a correlator, in which the channel estimator is used to estimate a channel response from a received signal. The channel response, together with an ideal channel response estimated based on the peak-detection method, are then used in the correlator to estimate a time delay.
Another example of a peak-detection estimator is disclosed in C. Falsi, D. Dardari, L. Mucchi, and M. Z. Win, “Time of arrival estimation for UWB localizers in realistic environments,” EURASIP J. Appl. Signal Processing, vol. 2006, pp. 1-13 (“Falsi”). In Falsi, three estimation strategies are disclosed for the peak detection estimator. The strategies are, in increasing complexity, (a) single-search (SS); (b) search-and-subtract (SaS); and (c) search-subtract-and-readjust (SSaR). The SS strategy does not require a complex computation process. Therefore, the SS strategy may be used as a very low complexity approach, which may be followed by the SaS and SSaR strategies, when necessary. However, none of the strategies give a good estimate under NLOS conditions, when the first arriving path is weak.
While most peak-detection TOA estimators have lower implementation complexity, relative to ML-based estimators, their performance degrades under low SNR conditions. Furthermore, peak-detection TOA estimators provide poor TOA estimates under NLOS conditions when the first arriving path is weak.
Still another example of a simple technique for detecting the first arriving path in a harsh propagation environment is to compare the output of the receiver with a threshold whose value is optimized according to the operating condition (e.g., SNR). Recently, threshold-based estimators (e.g., those disclosed in Dardari, above) are gaining interests. Other threshold-based estimator examples include (a) copending U.S. patent application (“Copending Application I”), entitled “Method for Optimum Threshold Selection of Time-of-Arrival Estimators,” by C.-C. Chong and F. Watanabe, Ser. No. 11/949,152, filed on Dec. 3, 2007, based on a U.S. provisional patent application Ser. No. 60/868,526, filed on Dec. 4, 2006; (b) I. Guvenc and Z. Sahinoglu, “Threshold-based TOA estimation for impulse radio UWB systems,” in Proc. IEEE Int. Conf. on Ultra-Wideband (ICU), Zurich, Switzerland, September 2005, pp. 420-425; (c) P. Cheong, A. Rabbachin, J. Montillet, K. Yu, and I. Oppermann, “Synchronization, TOA and position estimation for low-complexity LDR UWB devices,” in Proc. IEEE Int. Conf on Ultra-Wideband (ICU), Zurich, Switzerland, September 2005, pp. 480-484; and (d) A. Rabbachin, J.-P. Montillet, P. Cheong, A. Rabbachin, G. T. F. de Abreu, and I. Oppermann, “Non-coherent energy collection approach for TOA estimation in UWB systems,” in Proc. Int. Symp. on Telecommunications (IST), Shiraz, Iran, September 2005.
Threshold-based estimators are attractive because of their simple designs, as complexity and computational constraints are often critical considerations in applications such as those involving low cost battery-powered devices (e.g., in wireless sensor networks). However, despite the low implementation complexity, these techniques do not give optimum ranging accuracy especially under NLOS conditions. In particular, most threshold-based TOA estimators work efficiently only under high SNRs or with long observation times (i.e., long preambles). Under low SNRs or short observation times (i.e., short preambles), threshold-based estimators tend to be biased, with large corresponding mean-square errors (MSEs). The large MSEs result from adjacent peaks with similar height due to noise, multipath, and pulse side lobes, all of which engender ambiguity in the selection of the correct peak, and thus result in ranging accuracy degradation. However, UWB systems are intended to operate in multipath environments with low SNRs.
Conventional TOA estimation approaches provide interference/inter-path cancellation based on recognizing the shape of the band limited transmitted pulse. See, for example, R. Moddemeijer, “On the determination of the position of extrema of sampled correlators,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 39, no. 1, pp. 216-291, January 1991 (“Moddemeijer”). Moddemeijer's approach is robust, but does not lead to a significant improvement in initial TOA estimation. Another approach uses subspace techniques, such as disclosed in A. Jakobsson, A. L. Swindlehurst, and P. Stoica, “Subspace-based estimation of time delays and Doppler shift,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 46, no. 9, pp. 2472-2483, September 1998. The subspace-based TOA estimation is very complex, requiring generating correlation matrices and their inverses, and performing a large number of matrix multiplications. As demonstrated in M. Latva-aho, “Advanced receivers for CDMA systems,” Acta Uniersitatis Ouluensis, C125, pp. 179, subspaced-based estimators perform poorly in static or slow-moving channels. For example, the article “Superresolution of multipath delay profiles measured by PN correlation method,” by T. Manabe and H. Takai, IEEE Trans. Antennas Propagat., vol. 40, no. 5, pp. 500-509, May. 1992 (“Manabe”), illustrates a subspace technique using eigenvector decomposition. Manabe's TOA estimation approach requires complex steps for calculating eigenvectors of the channel correlation matrix.
In general, the TOA estimators described above (e.g., ML-based, peak-detection, and threshold-based estimators) fail to reliably provide robust and accurate TOA ranging information under NLOS conditions and multipath-rich environments. Some TOA-based techniques are only applicable for UWB based systems and time-domain modulation schemes. Therefore, a more robust TOA estimator that accurately estimates TOA information under NLOS condition is highly desired.